In airborne or model data, clouds are often defined using information about Liquid Water Content (LWC). Unfortunately LWC is not enough to retrieve information about the dynamical boundary of the cloud, i.e. volume of turbulent air around the cloud. In this work, we propose an algorithmic approach to this problem based on a method used in time series analysis of variables in dynamic systems, namely Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA). By studying RP’s constructed with turbulence kinetic energy, vertical velocity and temperature fluctuations and quantifying appropriate time series of laminarity (LAM) calculated using the plots, we distinguish between turbulent and non-turbulent segments along a horizontal flight leg.

The science guiding the \EURECA campaign and its measurements are presented. \EURECA comprised roughly five weeks of measurements in the downstream winter trades of the North Atlantic — eastward and south-eastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, \EURECA marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or, or the life-cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso (200 km) and larger (500 km) scales, roughly four hundred hours of flight time by four heavily instrumented research aircraft, four global-ocean class research vessels, an advanced ground-based cloud observatory, a flotilla of autonomous or tethered measurement devices operating in the upper ocean (nearly 10000 profiles), lower atmosphere (continuous profiling), and along the air-sea interface, a network of water stable isotopologue measurements, complemented by special programmes of satellite remote sensing and modeling with a new generation of weather/climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that \EURECA explored — from Brazil Ring Current Eddies to turbulence induced clustering of cloud droplets and its influence on warm-rain formation — are presented along with an overview \EURECA’s outreach activities, environmental impact, and guidelines for scientific practice.

The international field campaign for EUREC4A (Elucidating the role of clouds and circulation coupling in climate) gathered observations to better understand the links between trade-wind cumulus clouds, their organization, and larger scales, a large source of uncertainty in climate projections. A recent large-eddy simulation (LES) study showed a cloud transition that occurred during EUREC4A (2nd February 2020), where small shallow clouds developed into larger clouds with detrainment layers, was caused by an increase in mesoscale organization generated by a dynamical feedback in mesoscale vertical velocities. We show that kilometer-scale simulations with the Met Office Unified Model reproduce this increase in mesoscale organization and the process generating it, despite being much lower resolution. The simulations develop mesoscale organization stronger and earlier than the LES, more consistent with satellite observations. Sensitivity tests with a shorter spin-up time, to reduce initial organization, still have the same timing of development and sensitivity tests with cold pools suppressed show only a small effect on mesoscale organization. These results suggest that large-scale circulation, associated with an increased vertical velocity and moisture convergence, is driving the increase in mesoscale organization, as opposed to a threshold reached in cloud development. Mesoscale organization and clouds are sensitive to resolution, which affects changes in net radiation, and clouds still have substantial differences to observations. Therefore, while kilometer-scale simulations can be useful for understanding processes of mesoscale organization and links with large scales, including responses to climate change, simulations will still suffer from significant errors and uncertainties in radiative budgets.